Image-based hair modeling is an effective way to create high quality hair geometry. Hair acquisition techniques based on multi-view images often require complex equipment setups and long processing cycles (LUO, L., LI. H., AND RUSINKIEWICZ, S, 2013. Structure-aware hair capture. ACM Transactions on Graphics (TOG) 32, 4, 76.) (ECHEVARRIA, JI. BRADLEY, D., GUTIERREZ. D., AND BEELER, T. 2014. Capturing and stylizing hair for three-dimensional fabrication. ACM Transactions on Graphics (TOG) 33, 4, 125.) (HU, L., MA, C., LUO. L., AND LI, H. 2014. Robust hair capture using simulated examples. ACM Transactions on Graphics (TOG) 33, 4, 126.) (HU. L., MA. C., LUO, L., WEI. L.-Y. AND LI. H. 2014.Capturing braided hair styles. ACM Transactions on Graphics (TOG) 33, 6, 225.), thus, they are not suitable for average users, and are too costly for generating a large number of 3D hair models.
Recently. single-image based hair modeling techniques have yielded impressive results. The prior art achieves modeling by using different kinds of prior knowledge, such as layer boundary and occlusion (CHAI, M., WANG, L., WENG. Y., YU. Y., GUO. B., AND ZHOU, K. 2012. Single-view hair modeling for portrait manipulation. CM Transactions on Graphics (TOG) 31, 4, 116) (CHAI. M., WANG. L., WENG, Y., JIN. X., AND ZHOU, K. 2013. Dynamic hair manipulation in images and videos. ACM Transactions on Graphics (TOG) 32, 4, 75.), a 3D hair model database (HU, L., MA. C., LUO, L., AND LI, H. 2015. Single-view hair modeling using a hair style database. ACM Transactions on Graphics (TOG) 34, 4, 125.), and shadow cues (CHAI, M., LUO. L., SUNKAVALLI, K., CARR. N., HADAP. S., 747 AND ZHOU, K. 2015. High-quality hair modeling from a single portrait photo. ACM Transactions on Graphics (TOG) 34, 6, 204.). But these techniques all require different kinds of user interactions, for example, it is required to manually segment the hair from the image, or to provide strokes by a user to provide hair direction information, or to draw two-dimensional (2D) strands by a user to achieve retrieval. These user interactions typically take 5 minutes, and it takes about 20 minutes to generate a final result, which limits the generation of a large scale of hair models. Unlike the above methods, the present disclosure is fully automatic with high efficiency, and can handle a large number of images at the Internet level.